AI legal-risk assessment
Mapping the system, intended use, affected people, data inputs, outputs and decision points in order to identify the contracts, rights and liabilities that require control.
AI systems can affect confidential information, personal data, intellectual property, professional responsibility, evidence and civil liability. The legal structure should be designed before the tool becomes operationally critical.
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How the practice helps
AI procurement & contracts
Reviewing provider terms, warranties, data use, confidentiality, intellectual property, audit rights, service levels, indemnities and the allocation of responsibility for outputs.
Governance & internal policy
Designing proportionate rules for approved tools, sensitive information, human review, documentation, testing, escalation and accountability within the organisation.
AI disputes & liability
Analysing harmful or inaccurate outputs, automated decisions, deepfakes and other AI-related disputes by distinguishing the roles of provider, deployer, professional user and affected person.
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Legal context
AI law is already present in the rules that govern data, contracts and harm.
AI-related questions can engage existing rules on contract, civil responsibility, privacy, intellectual property, consumer protection, professional duties, evidence and private international law. Foreign regulatory duties may also matter when providers, users, data or affected markets are located outside Lebanon. A practical approach identifies the system’s real use and assigns responsibility across its lifecycle.
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Frequently asked questions
Direct questions deserve precise answers.
Does a business using AI need a written policy?
Where AI use is material, a proportionate policy can define approved tools, prohibited inputs, human-review requirements, recordkeeping, escalation and responsibility. The policy should reflect actual workflows rather than operate as a generic statement.
Who may be responsible when an AI output causes harm?
The answer depends on the facts and applicable law. The analysis may examine the provider, deployer, professional user and other actors, together with contractual allocation, control, foreseeability, fault, causation and the role of human review.
Can employees enter confidential information into public AI tools?
That may expose confidential, personal or protected information and create contractual or professional risks. Organisations should define which data may be used, with which tools, under what account settings and with what review and retention controls.
Professional enquiries
Discuss the legal structure of your digital matter.
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General information only. This page does not constitute legal advice and does not create an attorney–client relationship.